Aug 14, 2019 · In this work, we develop a distributed least squares approximation (DLSA) method that is able to solve a large family of regression problems.
In this work, we develop a distributed least-square approximation (DLSA) method that is able to solve a large family of regression problems (e.g., linear ...
Apr 13, 2021 · The proposed DLSA algorithm on the Spark system takes 26 minutes to obtain a logistic regression estimator, which is more efficient and memory.
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In this work, we develop a distributed least squares approximation (DLSA) method that is able to solve a large family of regression problems.
Jun 15, 2021 · In this work, we develop a distributed least squares approximation (DLSA) method that is able to solve a large family of regression problems ...
Apr 12, 2024 · In addition, we develop a variable selection procedure for the distributed modal regression under the robust least squares approximation ...
Jun 20, 2024 · This paper presents a distributed least-squares progressive iterative approximation (DLSPIA) method by dividing the collocation matrix into some blocks, which ...
Jul 6, 2023 · This paper proposes three distributed algorithms for solving linear algebraic equations to seek a least squares (LS) solution via multi-agent networks.
The method of least squares is a parameter estimation method in regression analysis based on minimizing the sum of the squares of the residuals.
Many centralized algorithms have been proposed to solve least-square problems in the literature, but not all of them can be implemented in distributed ...